In the past, computing applications such as computer games and multimedia applications used controllers, remotes, keyboards, mouse, or the like to allow users to manipulate game characters or other aspects of an application. More recently, computer games and multimedia applications have begun employing cameras and software gesture recognition to provide a human computer interface (“HCI”). With HCI, user gestures are detected, interpreted and used to control game characters or other aspects of an application.
Gesture based applications are fast catching up with all industry applications with a motto of removing man machine barrier. Today, most of the applications use gestures as a replacement to mouse/touch interface by mapping cursor to gestures. New applications/concepts like virtual environments are emerging that need to extend simple gestures based interaction to capture complex using continuous body tracking Some of the gesture detection devices (Kinect) allow body tracking using combinations of normal camera, IR (infrared) camera etc.
Applications that need continuous body detection for interaction need to be deployed carefully keeping field of focus, lighting, distance for interaction, multiple users etc. so that the application/system (user and application) can work effectively. However, the user while interacting (which requires movement to different positions) may lose the body tracking (BT) and continue to interact with applications assuming continuous BT leading to loss of functionalities. Mechanism for continuous body tracking is there but continues feedback for the level of tracking to the user is not available as of now.
In the light of the above drawbacks, it would be desirable to have a mechanism for continuous body tracking of the application to give user feedback and guidance on system readiness and effectiveness for interaction without any system/application training and no specified manual alignment of distance, lighting, etc.